Papers with Code 아카이브

Graph Neural Network

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

1

보존된 평가 기록

1

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/microsoft/tf-gnn-samples

공식 코드

GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation

https://github.com/mie-lab/ckg-traffic-forecasting

공식 코드

Context-aware knowledge graph framework for traffic speed forecasting using graph neural network

https://github.com/mieskolainen/hypertrack

공식 코드

HyperTrack: Neural Combinatorics for High Energy Physics

https://github.com/mikezchi/dcrnn-rv

공식 코드

Global Stock Market Volatility Forecasting Incorporating Dynamic Graphs and All Trading Days

https://github.com/mims-harvard/gnndelete

공식 코드

GNNDelete: A General Strategy for Unlearning in Graph Neural Networks

https://github.com/mingliangzhang2018/PGDP

공식 코드

Plane Geometry Diagram Parsing

https://github.com/miracle-2001/gnn4eeg

공식 코드

GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network

https://github.com/mirjanic/nar-latent-spaces

공식 코드

Latent Space Representations of Neural Algorithmic Reasoners

https://github.com/mit-tesse/dsg-rl

공식 코드

Hierarchical Representations and Explicit Memory: Learning Effective Navigation Policies on 3D Scene Graphs using Graph Neural Networks

https://github.com/mklab-iti/decentralized-gnn

공식 코드

p2pGNN: A Decentralized Graph Neural Network for Node Classification in Peer-to-Peer Networks

https://github.com/ml-postech/reverse-gnn

공식 코드

Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs

https://github.com/ml4bio/ribodiffusion

공식 코드

RiboDiffusion: Tertiary Structure-based RNA Inverse Folding with Generative Diffusion Models

https://github.com/ml4sci/qmlhep

공식 코드

Lie-Equivariant Quantum Graph Neural Networks

https://github.com/mlvlab/SELAR

공식 코드

Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning

https://github.com/mocherson/Exp_GNN

공식 코드

Towards Expressive Graph Representation

https://github.com/mocherson/MedGCN

공식 코드

MedGCN: Medication recommendation and lab test imputation via graph convolutional networks

https://github.com/mohbattharani/GVdoc

공식 코드

GVdoc: Graph-based Visual Document Classification

https://github.com/mojave-pku/TextLevelGCN

공식 코드

Text Level Graph Neural Network for Text Classification

https://github.com/mstubbemann/lg4av

공식 코드

LG4AV: Combining Language Models and Graph Neural Networks for Author Verification

https://github.com/mtandhj/sevo

공식 코드

Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution

https://github.com/mudit-dhawan/game-on

공식 코드

GAME-ON: Graph Attention Network based Multimodal Fusion for Fake News Detection

https://github.com/muhanzhang/IGMC

공식 코드

Inductive Matrix Completion Based on Graph Neural Networks

https://github.com/muhanzhang/SEAL

공식 코드

Link Prediction Based on Graph Neural Networks

https://github.com/muhanzhang/nestedgnn

공식 코드

Nested Graph Neural Networks

https://github.com/muyeby/RGAT-ABSA

공식 코드

Investigating Typed Syntactic Dependencies for Targeted Sentiment Classification Using Graph Attention Neural Network

https://github.com/mwcvitkovic/Deep_Learning_On_Code_With_A_Graph_Vocabulary--Code_Preprocessor

공식 코드

Open Vocabulary Learning on Source Code with a Graph-Structured Cache

https://github.com/myfatemi04/rl-deceptive-graph-planning

공식 코드

Deceptive Path Planning via Reinforcement Learning with Graph Neural Networks

https://github.com/n-gao/pesnet

공식 코드

Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions

https://github.com/nabavilab/multimodal-gnn-for-cancer-subtype-clasification

공식 코드

A Multimodal Graph Neural Network Framework of Cancer Molecular Subtype Classification

https://github.com/nadgeri14/KGPool

공식 코드

KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction

https://github.com/nargesnemati/mccl

공식 코드

Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust Recommendation

https://github.com/navid-naderi/LinkSchedulingGNNs_SupervisionStudy

공식 코드

Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision Levels

https://github.com/navid-naderi/Resilient_RRM_GNN

공식 코드

Learning Resilient Radio Resource Management Policies with Graph Neural Networks

https://github.com/navid-naderi/stateaugmented_rrm_gnn

공식 코드

State-Augmented Learnable Algorithms for Resource Management in Wireless Networks

https://github.com/ncfrey/litmatter

공식 코드

Scalable Geometric Deep Learning on Molecular Graphs

https://github.com/neelr/clamp

공식 코드

CLAMP: A Contrastive Language And Molecule Pre-training Network

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.